Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Engineer

Kraken
City of London
2 weeks ago
Create job alert
About Kraken

Kraken is the operating system for utilities of the future. Built in‑house at Octopus Energy, we took them to become the biggest supplier in the UK, and now we power energy companies and utilities around the globe—the company licences software to giants like Origin Energy in Australia and Tokyo Gas in Japan. We’re on a mission to accelerate the renewable transition, bringing affordable green energy to the world.


We’ve reinvented energy products with smart, data‑driven tariffs to balance customer demand with renewable generation, and Kraken’s platform controls more than half of the grid‑scale batteries in the UK. We’re driving the uptake of low‑carbon technologies such as solar panels and heat pumps through software for engineers in the field. Our suite of AI tools pioneers ML and AI to make agents’ lives easier and customers happier. We do this by hiring clever, curious, and self‑driven people, giving them modern tools, infrastructure and autonomy.


Our ML team consists of ML, front‑end and back‑end engineers, enabling us to prototype quickly and bring innovative tools into production at breakneck speed.


What you’ll do

  • Work with a high‑performance team of LLM, MLOps, backend and front‑end engineers
  • Tackle the biggest problems facing the company, giving a wide experience across the business and the freedom to define novel approaches
  • Help LLMs understand and interact with the millions of lines of code that run Kraken, leveraging GraphRAG, agentic workflows, finetuning, and reinforcement learning
  • Use classic ML and NLP techniques to complement and improve LLM systems
  • Act as a center of excellence for the whole business in AI, consulting other teams on LLM usage and lifting product quality across the organization
  • Stay at the forefront of understanding AI advancements and their technical implications for the team and business

What you’ll need

  • Curious and self‑driven – initiative to make decisions and find solutions to novel problems without excessive help
  • 1+ year experience with production‑level LLMs beyond POC and deep technical understanding of diverse technologies and techniques to adapt LLMs to domains (advanced RAG techniques, tool calling, finetuning, RL); interest in AI software copilots or autonomous engineering bots
  • 3+ years experience with traditional ML techniques, training and deploying non‑LLM models, and ongoing monitoring of production models incorporating feedback mechanisms to improve
  • A keen interest in Gen AI and classic ML, understanding emerging trends and research, and proven experience aligning and applying this to real world objectives

It would be great if you had

  • Experience working with large codebases and collaborating with multiple engineering teams in large companies
  • Experience in diverse LLM deployment methods (hosted finetuned models via services like Bedrock, and running directly via engines like vLLM)

Culture & Perks

Kraken is a certified Great Place to Work in France, Germany, Spain, Japan and Australia. In the UK we are one of the Best Workplaces on Glassdoor with a score of 4.7.


We aim to create an inclusive environment. Please contact if you need accommodations or have preferences to customise the interview process.


Equal Opportunity Employer

We consider all applicants without regard to race, colour, religion, national origin, age, sex, gender identity or expression, sexual orientation, marital or veteran status, disability, or any other legally protected status. U.S. based candidates can learn more about their EEO rights here.


Applicant Notice

Our Applicant and Candidate Privacy Notice and Artificial Intelligence Notice, Website Privacy Notice and Cookie Notice govern the collection and use of your personal data in connection with your application and use of our website. These policies explain how we handle your data and outline your rights under applicable laws, including GDPR and CCPA. If you would like more information about how your data is processed, please contact us.


Hiring Process

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans.


#J-18808-Ljbffr

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.